NSF Postdoctoral Fellowship in Biology: Identifying and Validating Missing Links in the Global Bat-Virus Network

Betke, Briana, Austin TX

Investigators

Abstract

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2023, Broadening Participation of Groups Underrepresented in Biology. The Fellowship supports a research and training plan for the Fellow that will increase the participation of groups underrepresented in biology. There is a pressing need to identify unobserved host-virus associations, as many infectious diseases of concern in humans, domestic animals, and wildlife are caused by viruses. However, predicting these interactions is challenged by a sparsity of information on known associations due to high logistical costs. Developing computer-based models to identify likely associations can cut costs by focusing field research efforts to test predicted interactions. This project will use predictive models to identify associations between bats and viruses, which will then be tested by field research. The research results will provide confirmation (or not) of bat-virus associations that will improve the predictive model. The fellow will broaden participation of underrepresented groups in biology through mentorship, a series of graduate school preparation workshops, and community outreach. The fellow will combine machine learning and systematic validation field and laboratory studies to expand the global bat–virus network and test the importance of bat roosting ecology relative to other bat and virus traits. Bats are of particular interest because they are known to host many viruses of zoonotic potential, leading to increased pathogen surveillance, and show intraspecific variation in roost preference for anthropogenic structures that could increase spillover opportunities to or from humans. The fellow will quantify the probability of interactions between bat species and virus families with link prediction models and then test these predictions as well as assess intraspecific variation in associations across roost structure type (anthropogenic or natural) in bats sampled in Oklahoma and Texas. Creating an iterative loop of model prediction, validation, and improvement is often a neglected step to accurate and adaptive modeling. To address this, the link prediction model will be run again with an updated dataset containing the validated predictions, and changes in model performance will be evaluated. To broaden participation of underrepresented groups in biology, the fellow will mentor students and present a series of workshops about undergraduate research, the graduate student experience, and career exploration at the University of Oklahoma. Additionally, the fellow will engage in community outreach through education of community volunteers on bat roosting ecology, wildlife disease ecology, and/or urban mammals. This project is jointly funded by the Division of Biological Infrastructure in the Directorate for Biological Sciences, and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.